setwd("~/Desktop/working-with-lyle/Formality_Project")#set our WD
if (!require("pacman")) install.packages("pacman") #run this if you don't have pacman
library(pacman)
pacman::p_load(tidyverse,rlang, zoo, lubridate, plotrix, ggpubr, caret, broom, kableExtra, reactable, install = T)
#use pacman to load packages quickly palette_map = c("#3B9AB2", "#EBCC2A", "#F21A00")
palette_condition = c("#ee9b00", "#bb3e03", "#005f73")
plot_aes = theme_classic() +
theme(legend.position = "top",
legend.text = element_text(size = 12),
text = element_text(size = 16, family = "Futura Medium"),
axis.text = element_text(color = "black"),
axis.line = element_line(colour = "black"),
axis.ticks.y = element_blank()) table_model = function(model_data) {
model_data %>%
tidy() %>%
rename("SE" = std.error,
"t" = statistic,
"p" = p.value) %>%
kable() %>%
kableExtra::kable_styling()
}df <- read_csv('Atlantic_Cleaned_all_vars.csv') #read in the data tidy_df <- df %>%
group_by(Date) %>% ###grouping by the year
mutate_at(vars("Analytic","WPS","BigWords","Period","readability","grade_level"), as.numeric) %>%
summarise_at(vars("Analytic","WPS","BigWords","Period","readability","grade_level"), funs(mean, std.error),)
#create center variables
tidy_df$Analytic_centered <- tidy_df$Analytic_mean - 85.94
tidy_df$WPS_centered <- tidy_df$WPS_mean - 37.14
tidy_df$BigWords_centered <- tidy_df$BigWords_mean - 25.68
tidy_df$Period_centered <- tidy_df$Period_mean - 4.589
tidy_df$readability_centered <- tidy_df$readability_mean - 57.45
tidy_df$grade_level_centered <- tidy_df$grade_level_mean - 10.71Flesch-Kincaid Ease of Readability: higher scores indicate material that is easier to read; lower numbers mark passages that are more difficult to read.
The Flesch–Kincaid Grade Level Score: presents a score as a U.S. grade level, making it easier for teachers, parents, librarians, and others to judge the readability level of various books and texts.
df %>%
select(Date) %>%
range()## [1] 1857 2022
df %>%
select(Filename) %>%
dplyr::summarize(n = n()) %>%
reactable::reactable(striped = TRUE)articles_year <- df %>%
select(Filename,Date) %>%
unique() %>%
group_by(Date) %>%
dplyr::summarize(n = n()) %>%
reactable::reactable(striped = TRUE)
articles_yearPlease see attached files for the graphs if needed.
#Plot our smoothed data
#we are using Non-tidy data here to capture the individual variation
#readability
readability_smooth <- ggplot(data=df, aes(x=Date, y=readability, group=1)) +
ggtitle("Readability") +
geom_point(color = "dodgerblue3", alpha = 0.5) +
geom_smooth(method = "loess", span = 0.50 )+
plot_aes +
labs(x = "Year", y = 'Ease of Readability') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold")) +
annotate(geom="text",x=1855,
y=25,label="
estimate = -0.1119
p-value < 0.001
", size = 3.5)
#grade level
grade_level_smooth <- ggplot(data=df, aes(x=Date, y=grade_level, group=1)) +
ggtitle("Reading Grade Level") +
geom_point(color = "dodgerblue3", alpha = 0.5) +
geom_smooth(method = "loess", span = 0.60 )+
plot_aes +
labs(x = "Year", y = 'Reading Grade Level') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold")) +
annotate(geom="text",x=1855,
y=22,label="
estimate = 0.0138
p-value < 0.001
", size = 3.5)
smooth_graphs <- ggpubr::ggarrange(readability_smooth,grade_level_smooth,ncol=1, nrow=2, common.legend = TRUE, legend = "bottom")
annotate_figure(smooth_graphs,
top = text_grob("Smooth Flesch-Kincaid Graphs", color = "black", face = "bold", size = 20),
bottom = text_grob(
"Note. Horizontal shading represents Standard Error."
, color = "Black",
hjust = 0.9, x = 1, face = "italic", size = 12))readability_smooth_tidy <- ggplot(data=tidy_df, aes(x=Date, y=readability_mean, group=1)) +
ggtitle("Readability") +
geom_point(color = "dodgerblue3", alpha = 0.7) +
geom_smooth(method = "loess", span = 0.60 )+
plot_aes +
labs(x = "Year", y = 'Ease of Readability') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold")) +
annotate(geom="text",x=1855,
y=60,label="
estimate = -0.079
p-value < 0.001
", size = 3.5)
grade_smooth_tidy <- ggplot(data=tidy_df, aes(x=Date, y=grade_level_mean, group=1)) +
ggtitle("Grade Level") +
geom_point(color = "dodgerblue3", alpha = 0.7) +
geom_smooth(method = "loess", span = 0.80 )+
plot_aes +
labs(x = "Year", y = 'Grade Level Score') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold")) +
annotate(geom="text",x=1855,
y=12,label="
estimate = 0.0138
p-value < 0.001
", size = 3.5)
tidy_smooth_graphs <- ggpubr::ggarrange(readability_smooth_tidy,grade_smooth_tidy, ncol=1, nrow=2, common.legend = TRUE, legend = "bottom")
annotate_figure(tidy_smooth_graphs,
top = text_grob("Smoothed Graphs (grouped by year)", color = "black", face = "bold", size = 20),
bottom = text_grob(
"Note. Horizontal shading represents Standard Error.
Estimates are from mean-centered analyses (data centered on means for 1857"
, color = "Black",
hjust = 1, x = 1, face = "italic", size = 12))Readability <- ggplot(data=tidy_df, aes(x=Date, y=readability_mean, group=1)) +
geom_line(colour = "dodgerblue3") +
geom_ribbon(aes(ymin=readability_mean-readability_std.error, ymax=readability_mean+readability_std.error), alpha=0.2) +
ggtitle("Readbility") +
plot_aes +
labs(x = "Year", y = 'Ease of Readbility') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold"))
grade_level <- ggplot(data=tidy_df, aes(x=Date, y=grade_level_mean, group=1)) +
geom_line(colour = "dodgerblue3") +
geom_ribbon(aes(ymin=grade_level_mean-grade_level_std.error, ymax=grade_level_mean+grade_level_std.error), alpha=0.2) +
ggtitle("Grade Level") +
plot_aes +
labs(x = "Year", y = 'Flesch-Kincaid Grade Level') +
theme(axis.text.x=element_text(angle=45, hjust=1),
plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 16)) +
theme(axis.text=element_text(size=16),
axis.title=element_text(size=20,face="bold"))+
theme(plot.title.position = 'plot',
plot.title = element_text(hjust = 0.5, face = "bold", size = 20)) +
theme(axis.text=element_text(size = 14),
axis.title=element_text(size = 20,face="bold"))
#raw graphs
raw_graphs <- ggpubr::ggarrange(Readability, grade_level, ncol=1, nrow=2, common.legend = TRUE, legend = "bottom")
annotate_figure(raw_graphs,
top = text_grob("Raw Flesch-Kincaid Graphs (grouped by year)", color = "black", face = "bold", size = 20),
bottom = text_grob("Note. Horizontal shading represents Standard Error.
)"
, color = "Black",
hjust = 1.3, x = 1, face = "italic", size = 16))Results presented: Raw data, aggregated by year, centered on 1857
#Raw Data
Readability_RAW <- lm(readability ~ Date, data = df)
#Tidy Data
Readability_TIDY <- lm(readability_mean ~ Date, data = tidy_df)
#Centered
Readability_centered <- lm(readability_centered ~ Date, data = tidy_df)
table_model(Readability_RAW)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | 282.2207 | 9.6271 | 29.32 | 0 |
| Date | -0.1119 | 0.0049 | -22.71 | 0 |
table_model(Readability_TIDY)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | 221.108 | 19.5255 | 11.324 | 0 |
| Date | -0.079 | 0.0101 | -7.851 | 0 |
table_model(Readability_centered)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | 163.658 | 19.5255 | 8.382 | 0 |
| Date | -0.079 | 0.0101 | -7.851 | 0 |
Models presented in order: Raw data, aggregated by year, centered on 1857
#Raw Data
Grade_RAW <- lm(grade_level ~ Date, data = df)
#Tidy Data
Grade_TIDY <- lm(grade_level_mean ~ Date, data = tidy_df)
#Centered
Grade_centered <- lm(grade_level_centered ~ Date, data = tidy_df)
table_model(Grade_RAW)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | -25.2049 | 2.0722 | -12.16 | 0 |
| Date | 0.0176 | 0.0011 | 16.55 | 0 |
table_model(Grade_TIDY)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | -18.3108 | 3.7717 | -4.855 | 0 |
| Date | 0.0138 | 0.0019 | 7.098 | 0 |
table_model(Grade_centered)| term | estimate | SE | t | p |
|---|---|---|---|---|
| (Intercept) | -29.0208 | 3.7717 | -7.694 | 0 |
| Date | 0.0138 | 0.0019 | 7.098 | 0 |